ABSTRACT:
A
significant category of application performance problems actually arise
from the underlying runtime system. The current generation of
performance tools is not able to accurately diagnose the root cause of
such problems, often incorrectly attributing them to the application
code itself. We are developing a new approach to automated
performance debugging; Environment Aware Performance Diagnosis (EAPD),
that can detect and correct interference between the runtime
environment and high end applications and thereby substantially improve
performance. Our approach allows us to remove bottlenecks that
current tools cannot identify, or worse, that they misdiagnose.
For example, existing tools will often diagnose a high interrupt rate
as a load imbalance in the application rather than correctly detecting
that certain processors are being used for scheduled system activities
or that failing hardware is interrupting excessively. EAPD will
allow developers to optimize application use of runtime
systemresources. By combining the appropriate data from the
environment, the application, and the runtime system, EAPD will enable
a more effective and scalable performance diagnosis tool. Our
techniques target system software for Petascale platforms of the near
future, including the Cray XT systems, Linux clusters, and IBM Blue
Gene platforms. In this talk I will describe our future
vision and our early results on the project.
BIO:
Karen L. Karavanic is an Associate Professor of Computer Science at
Portland State University in Oregon, where she runs the High
Performance Computing Laboratory and teaches a variety of courses in
Operating Systems, Performance Measurement and Analysis, and High End
Computing. She received her B.A. in Computer Science from New
York University; and her M.S. and Ph.D. in Computer Science from the
University of Wisconsin - Madison.
# # #